Virtualization technology is a disruptive business model that can drive significant cost savings. In a virtualized data center a single server hosts multiple workloads each running on a separate virtual machines (VMs). Virtualization software allow partitioning and sharing of computational resource of a server among different VMs. Partitioning of resources is useful to ensure the performance isolation among the VMs and resource shaping happens by multiplexing the workload of different VMs. Present virtualized environment hosting multiple physical machines and multiple workloads are faced with the challenge of appropriately sizing and placing of the VMs that host them on the physical infrastructure.
There are existing models and methods to address the optimal VM resource allocation. But these have a major drawback. All the existing approaches assume a fixed threshold above which the sharing possibilities between workloads are computed. This fixed threshold value assumption results in sub-optimal solution, as the opportunities of sharing based on the time varying nature of co-located workload is never exploited fully.